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The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients

BACKGROUND: Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-...

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Autores principales: Hodgson, Luke E., Roderick, Paul J., Venn, Richard M., Yao, Guiqing L., Dimitrov, Borislav D., Forni, Lui G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082509/
https://www.ncbi.nlm.nih.gov/pubmed/30089118
http://dx.doi.org/10.1371/journal.pone.0200584
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author Hodgson, Luke E.
Roderick, Paul J.
Venn, Richard M.
Yao, Guiqing L.
Dimitrov, Borislav D.
Forni, Lui G.
author_facet Hodgson, Luke E.
Roderick, Paul J.
Venn, Richard M.
Yao, Guiqing L.
Dimitrov, Borislav D.
Forni, Lui G.
author_sort Hodgson, Luke E.
collection PubMed
description BACKGROUND: Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. METHODS AND FINDINGS: A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014–16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981–1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858–0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560–0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. CONCLUSIONS: In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness. TRIAL REGISTRATION: Clinicaltrials.org NCT03047382.
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spelling pubmed-60825092018-08-30 The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients Hodgson, Luke E. Roderick, Paul J. Venn, Richard M. Yao, Guiqing L. Dimitrov, Borislav D. Forni, Lui G. PLoS One Research Article BACKGROUND: Acute kidney injury (AKI) is assoicated with high mortality and measures to improve risk stratification and early identification have been urgently called for. This study investigated whether an electronic clinical prediction rule (CPR) combined with an AKI e-alert could reduce hospital-acquired AKI (HA-AKI) and improve associated outcomes. METHODS AND FINDINGS: A controlled before-and-after study included 30,295 acute medical admissions to two adult non-specialist hospital sites in the South of England (two ten-month time periods, 2014–16); all included patients stayed at least one night and had at least two serum creatinine tests. In the second period at the intervention site a CPR flagged those at risk of AKI and an alert was generated for those with AKI; both alerts incorporated care bundles. Patients were followed-up until death or hospital discharge. Primary outcome was change in incident HA-AKI. Secondary outcomes in those developing HA-AKI included: in-hospital mortality, AKI progression and escalation of care. On difference-in-differences analysis incidence of HA-AKI reduced (odds ratio [OR] 0.990, 95% CI 0.981–1.000, P = 0.049). In-hospital mortality in HA-AKI cases reduced on difference-in-differences analysis (OR 0.924, 95% CI 0.858–0.996, P = 0.038) and unadjusted analysis (27.46% pre vs 21.67% post, OR 0.731, 95% CI 0.560–0.954, P = 0.021). Mortality in those flagged by the CPR significantly reduced (14% pre vs 11% post intervention, P = 0.008). Outcomes for community-acquired AKI (CA-AKI) cases did not change. A number of process measures significantly improved at the intervention site. Limitations include lack of randomization, and generalizability will require future investigation. CONCLUSIONS: In acute medical admissions a multi-modal intervention, including an electronically integrated CPR alongside an e-alert for those developing HA-AKI improved in-hospital outcomes. CA-AKI outcomes were not affected. The study provides a template for investigations utilising electronically generated prediction modelling. Further studies should assess generalisability and cost effectiveness. TRIAL REGISTRATION: Clinicaltrials.org NCT03047382. Public Library of Science 2018-08-08 /pmc/articles/PMC6082509/ /pubmed/30089118 http://dx.doi.org/10.1371/journal.pone.0200584 Text en © 2018 Hodgson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hodgson, Luke E.
Roderick, Paul J.
Venn, Richard M.
Yao, Guiqing L.
Dimitrov, Borislav D.
Forni, Lui G.
The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title_full The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title_fullStr The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title_full_unstemmed The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title_short The ICE-AKI study: Impact analysis of a Clinical prediction rule and Electronic AKI alert in general medical patients
title_sort ice-aki study: impact analysis of a clinical prediction rule and electronic aki alert in general medical patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082509/
https://www.ncbi.nlm.nih.gov/pubmed/30089118
http://dx.doi.org/10.1371/journal.pone.0200584
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